Systems and methods for assessing and improving sustained attention

ABSTRACT

The present invention relates to a system and method for assessing and training the quality of attentional awareness and control of an individual. The individual&#39;s attention is monitored using a neurophysiological system such as EEG while using a computer system and display that provides signals that allow the correlation of behavioral measures of attention with neurophysiological measures. The combination of those signals is a novel, accurate and reliable system for assessing any individual&#39;s true attention capabilities.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.16/428,955, filed May 31, 2019, recently allowed, which application is adivisional of U.S. patent application Ser. No. 15/090,586, filed Apr. 4,2016, now U.S. Pat. No. 10,342,472 issued Jul. 9, 2019, which is anon-provisional and claims the benefit of U.S. Provisional ApplicationNo. 62/143,704 filed Apr. 6, 2015, expired, of the same title. Also,U.S. patent application Ser. No. 15/090,586 is a continuation-in-part ofU.S. application Ser. No. 13/933,024, filed Jul. 1, 2013, entitled“Systems and Methods for Training Meta-Attention”, now U.S. Pat. No.9,378,658, issued Jun. 28, 2016, which is hereby fully incorporated byreference, which applications and patents are incorporated herein intheir entirety by this reference.

BACKGROUND

The present invention relates to systems and methods for monitoring andtraining sustained attention of users.

Sustained attention is important because it is the foundation for beingfocused, effective and productive in nearly every cognitive process weuse in everyday life (effective, productive); it is also a significantcomponent of many cognitive clinical disorders (e.g. ADHD, autism,schizophrenia, depression, SAD, PTSD, TBI).

Continuous Performance Tests (CPTs) have proven useful as assessmenttools in normal populations and for assessing the clinical disordersmentioned above. A major limitation has been in their ability to assessthe suppression of distractors. Using behavioral tests, in whichdistractors are by definition irrelevant and not to be responded to, onecan assess a person's ability to ignore distractors only indirectly—bydetecting the rare instance when a person responds incorrectly to adistractor which is indicative of less attention to the target and/orless suppression of the distractor (although which is the cause isambiguous). Consequently, the data includes a small quantity of rareerrors. Poor distractor suppression can also be indirectly inferred bymeasuring differences in performance to a target as a function of thepresence of distractors (e.g., when a target is preceded by a distractorversus when it is not preceded by a distractor). Therefore, CPT tests donot provide a direct measure of continuous suppression of distractors.The only way to obtain such a measure is with brain physiology measures.

In well-accepted models of attention and behavioral studies, it has beenrecognized that enhanced processing of targets and suppression ofdistractors are not simply opposite sides of the same attention coin. Ithas always been difficult to characterize the processing of distractorsbehaviorally because it must be accomplished indirectly (e.g.,distractor disruption of performance to target; occasional errors, falsealarms to non-targets; etc.). Using neurophysiological measures we candirectly measure the processing of all distractors as well as targetprocessing. We now know that attending and suppressing distractors areat least partially separable functions that are controlled in part bydifferent brain regions. EEG and fMRI literature shows that deficits inattending vs. distractor suppression can be differentiated behaviorallyand physiologically. Consequently, it makes sense that these processescan be differentiated within an individual and that they can contributedifferentially to cognitive disorders. The important implication for theprescription of therapeutics is that therapeutics can be tailored toattention processes or distractor suppression processes, or both.

Two people can perform comparably with different configurations of brainprocesses. For example, one person may enhance target processing withlittle suppression of distractors, while the other person has littleenhancement of target processing and strong suppression of competingdistractor inputs. In both cases the target processing wins over thedistractor processing and the result is a similar output measure (e.g.,RT). However, the same training or therapeutic that addresses, forexample, target processing would likely result in quite differentchanges in these people. Ideally, training would focus on attending forone person and ignoring (distractor suppression) for the other. Wepropose an assessment tool that characterizes both attending andignoring will open the door to the development of new cognitive trainingand therapeutics that can emphasize these two related yet separableaspects of sustained attention.

Being able to continuously monitor performance and brain components ofattending and ignoring opens the door for training/therapeutics thatprovides ongoing feedback during sustained attention tasks. This isessential to creating improved awareness of attention (meta-attention)and attentional control.

Consequently, it is apparent that an urgent need exists for the abilityto determine an individual's “brain style”, often referred to as“executive function”, so that therapeutics can be applied that targetone or the other aspect of attending/ignoring processes.

SUMMARY

To achieve the foregoing and in accordance with the present invention, asystem and method for continuous monitoring and assessment of attentionand improvement of attentional awareness and control is provided. Inparticular the system and methods for monitoring and assessment includean EEG system that allows for the continuous monitoring of brainactivity. That EEG system has enough leads to reliably detect a steadystate visually evoked potential (SSVEP) that is induced by a flickeringimage. That flickering image is presented to the individual through acomputer screen and the flicker rate can vary widely, from 5 to 60hertz.

As the individual is visually engaged with the screen, the flicker ratecreates a signal of equivalent frequency that can be detected directly.In this embodiment, the screen presents two objects flickering atdifferent rates. Both objects are in the visual field simultaneously.The individual is instructed to attend to one of the objects and ignorethe other object.

Over the time frame of the assessment, a series of targets anddistractors are presented to the individual in conjunction with theobjects being attended or ignored. The individual is instructed tophysically respond to only the targets presented in conjunction withattended object. All other distractors and targets are to be ignored andthe individual is instructed to not physically respond.

During the assessment, the user is given a visual “fixation point” thatthe user is visually focused on so that to ignore and attend objects arein a clear visual field.

A computer monitors continuously the individual's behavioral responsesand also their EEG signals. The assessment algorithm uses both data setsto make reliable and accurate measurements of the individual's abilityto attend and ignore.

Repeated use of the method can constitute training of attentionalawareness (meta-attention) and feedback about attending and ignoringbrain activity levels can be used to train the user's attentionalawareness and control.

Note that the various features of the present invention described abovemay be practiced alone or in combination. These and other features ofthe present invention will be described in more detail below in thedetailed description of the invention and in conjunction with thefollowing figures.

BRIEF DESCRIPTION OF THE DRAWINGS

In order that the present invention may be more clearly ascertained,some embodiments will now be described, by way of example, withreference to the accompanying drawings, in which:

FIG. 1A illustrates one embodiment of an attention measuring system inaccordance with the present invention;

FIG. 1B is a top view of a user's head with exemplary locations formeasuring SSVEP and/or SSAEP;

FIG. 2 is a flow diagram of an exemplary testing protocol for theembodiment of FIG. 1A;

FIGS. 3A-3C and 4A-4C are screenshots illustrating exemplary protocolsfor the embodiment of FIG. 1A;

FIG. 5 is an exemplary flow diagram of an exemplary training protocolfor the embodiment of FIG. 1A; and

FIG. 6 is another exemplary flow diagram of a second exemplary trainingprotocol for the embodiment of FIG. 1A.

DETAILED DESCRIPTION

The present invention will now be described in detail with reference toseveral embodiments thereof as illustrated in the accompanying drawings.In the following description, numerous specific details are set forth inorder to provide a thorough understanding of embodiments of the presentinvention. It will be apparent, however, to one skilled in the art, thatembodiments may be practiced without some or all of these specificdetails. In other instances, well known process steps and/or structureshave not been described in detail in order to not unnecessarily obscurethe present invention. The features and advantages of embodiments may bebetter understood with reference to the drawings and discussions thatfollow.

Aspects, features and advantages of exemplary embodiments of the presentinvention will become better understood with regard to the followingdescription in connection with the accompanying drawing(s). It should beapparent to those skilled in the art that the described embodiments ofthe present invention provided herein are illustrative only and notlimiting, having been presented by way of example only. All featuresdisclosed in this description may be replaced by alternative featuresserving the same or similar purpose, unless expressly stated otherwise.Therefore, numerous other embodiments of the modifications thereof arecontemplated as falling within the scope of the present invention asdefined herein and equivalents thereto. Hence, use of absolute and/orsequential terms, such as, for example, “will,” “will not,” “shall,”“shall not,” “must,” “must not,” “first,” “initially,” “next,”“subsequently,” “before,” “after,” “lastly,” and “finally,” are notmeant to limit the scope of the present invention as the embodimentsdisclosed herein are merely exemplary.

The present invention relates to a system and methods for an objective,reliable and accurate assessment of an individual's attention. Forexample, Attention-Deficit/Hyperactivity Disorder (ADHD) is highlyprevalent, and the methods for characterization of the disorder arelimited, particularly with respect to neurophysiological biomarkers thatcan be made readily and inexpensively accessible to a wide market. Wehave created a novel neurophysiological attention test (NAT) based onelectroencephalography (EEG) and we have successfully demonstrated theNAT's validity and utility as an assessment tool for ADHD providing twonew biomarkers for ADHD The NAT provides critical new measures of thefluctuations in attentional control in ADHD in addition to standardperformance measures. The neurophysiological measures of the NAT providea closer link to brain research and brain-based models of ADHD andprovide direct brain measures of treatment effects.

Attention-related deficits in ADHD are associated more with sustainedattention than with selective. Deficits in selective attention, i.e. thetop-down controlled processing of a target or distractor, are lessprevalent under circumstances in which patients with ADHD properlyallocate attentional control (e.g., high load). ADHD individual deficitslie in the ability to be consistently and purposefully in control ofthese top-down controlled selective attention processes. That is, animportant aspect of ADHD would appear to be difficulty in themaintenance of attentional control. Deficits in maintaining attentionalcontrol manifest as inconsistent intra-individual performance onsustained attention tasks with periods of normal performance and otherperiods of poor performance thought to reflect “inattention”, andconsidered by several groups to be an important component of ADHD. Suchlapses in attention would result in the common finding of fluctuationsin reaction time (intra-individual RT variability), which we find in ourNAT performance measures, recently characterized as infra-slow frequencyoscillations. A logical step in relating these performance fluctuationsto brain processes is to examine large-scale brain networks known tohave similarly infra-slow fluctuations in activity. There is fMRIevidence for decreased coherence within the default network and lesssuppression of default network activity during external tasks in ADHD.Given the putative relationships between default network and attentionalcontrol networks, these results suggest there may be alterations inattention control networks as well. Hence, investigation of possiblechanges in slow fluctuations in attention control networks and theirrelationship to attentional lapses in ADHD, and emphasizes the need forintra-individual measures of brain processes over time to characterizethe neural fluctuations of attentional control during sustainedattention.

Cognitive neuroscience studies have clearly identified two functional,and neurally distinct, components of attentional control: top-downcontrolled enhancement of attended targets and top-down controlledsuppression of ignored distractors. Subjective assessments indicatedistractability to be a key factor in ADHD, and a recent objective studyhas demonstrated that individuals with ADHD have a deficit in therecruitment of attentional control over target processing andsuppression of distractors. While the latter study used behavioralmeasures, it has been shown that patients (elderly with cognitivedecline) can be differentiated on the basis of fMRI-based brain measuresof distractor suppression versus target enhancement, demonstrating thatthese separate top-down control systems can be altered independently aswell. This implies a need for intra-individual measures of brainprocesses over time to characterize maintenance of both processes:attending targets and ignoring distractors. Objective assessment testsmust obtain brain measures of both components of attentional control andtheir intra-individual fluctuations during sustained attention.Detecting fluctuations over time requires continuous measures of bothtarget and distractor processing. Doing so improves diagnostics andmonitoring of the brain effects of treatment.

Unlike any other behavioral or EEG-based assessment methods of ADHD, ourNeurophysiological Attention Test (NAT) utilizes a novel EEG method tomeasure infra-slow fluctuations in BOTH attending and ignoringsimultaneously during sustained attention tasks.

The NAT is the first EEG-based method for continuously trackingneurophysiological indices of attending targets and ignoring distractorssimultaneously during sustained attention tasks. We adapt thesteady-state visual evoked potential (SSVEP) method to take advantage ofthe fact that the magnitude of stimulus processing in sensory cortex(measured by the SSVEP) provides an index of attentional top-downcontrol from frontal-parietal systems. Our method makes it possible forthe first time to continuously measure the intra-individual variability(infra-slow fluctuations) of electrophysiological brain activityrepresenting the top-down controlled processing of BOTH attended targetsand of ignored distractors in ADHD. Measurements of infra-slowfluctuations can also be fMRI-based.

Our innovation is to use the time-proven SSVEP frequency taggingmeasures, and for the first time in a continuous mode to trackinfra-slow fluctuations (˜0.1-0.02 Hz) in control over both sustainedattending and sustained ignoring throughout continuous attention tasks(FIG. 1 ). To do this we measure activity reflecting the processing oftwo different stimuli (target and distractor) concurrently. However, itis challenging to define EEG measures that can be used unambiguously tomeasure the responses to each of multiple stimuli presentedsimultaneously. The SSVEP frequency tagging method allows the attendedtarget signal and the ignored distractor signal to be identified by thefrequency of the SSVEP. Each stimulus type (target, distractor) isassigned a flicker frequency (e.g., 15, 17 Hz respectively) that drivesvisual sensory cortices at the flicker frequency of each stimulus,thereby isolating and stabilizing the EEG activity corresponding to eachstimulus type even when they are presented at the same time or even inthe same location, e.g. in figure/background configuration. It is theinfra-slow fluctuations in attending and ignoring that one can be awareof (meta-attention), and thus these measures can be used for assessmentof meta-attention and for feedback about attending and ignoring andtraining meta-attention to improve attentional control. Many patients,for example those with ADHD, stress, anxiety and depression, have lessmeta-attention, i.e. they are less self-aware of their attention, or areless frequently self-aware of their attention. This results in negativesymptoms and decrement of quality of life. Improving theirmeta-attention and thereby also their attentional control can greatlybenefit these patients.

The NAT also provides behavioral performance data during the sustainedattention task. Our findings from the NIH award are consistent with theliterature on altered intra-individual reaction time variability,showing increased ultra-slow fluctuations in reaction time (0.05-0.1 Hz)in ADHD (see Appendix A). In this NIH Small Business Innovation ResearchAward we showed that the combination of our behavioral andelectrophysiological measures was better than the current gold standardassessment method (Conners CPT test) for diagnosis of ADHD.

In accordance to the embodiments of the present invention, in additionto relating physiological indices to performance, the physiologicalindices themselves have functional significance. In fact, they canuncover important brain function differences, in the presence of similarbehavioral measures, that can be differentially targeted bytherapeutics. At a minimum, they can provide additional, otherwiseunavailable, information to behavioral measures that may not completelydifferentiate sub-groups of patients (but suggest that there may besub-groups), to aid in that differentiation.

This represents both significance and innovation because it will impactthe field (significance)—drive development of new therapeutics; and itsnovel/innovative approach will impact thinking in the field and isexpected to generate new lines of research and development of new typesof therapeutics. The method not only significantly improves assessmentand therapeutics; but it can open the door to new categorization ofindividuals and patients, and to the development of a new line oftherapeutics.

One good example of how suppression of distractors is important is, ifyou do not suppress distractors well, then they get into working andshort term memory and interfere with long-term formation of memories forrelevant information, and contribute to confusion. It is likely thatless suppression of distractors could lead to shifts in attention awayfrom relevant information. There are multiple cognitive disorders wherethis type of problem is a contributing factor and it impacts performanceand well being in everyone.

Five key advantages include: (1) Capability to measure fluctuations inperformance continuously over time to track performance-related aspectsof sustained attention. (2) Capability to simultaneously andcontinuously track a physiological index of the attended channel ofinformation during the task, and (3) the physiological index of theignored/distractor channel of information. (4) Capability to relate theindices for the attended and ignored channels of processing to eachother and to performance. (5) Capability to provide feedback about theseindices to the user.

Decomposing the physiological/functional components contributes toperformance. Performance can be decomposed into attention relatedenhancement of target processing and distractor suppressioncontributions.

In addition, these performance measures do not disrupt and re-setattention like CPT tasks that utilize no-go stimuli (e.g., Conners CPT;SART). Note that mental drifting is disrupted and attention is therebyre-set in terms of RT when a rare no-go stimulus occurs within ago/no-go task. However, by disrupting natural attentional drift, onegreatly diminishes the ability to continuously track natural waxing andwaning of attention.

The major advantages of these methods are that they measure bothattention related processing and distractor processing directly (notinferred), simultaneously, and continuously. In addition, the samemeasures are used for both attended processing and distractorprocessing, i.e. there are not two different types of measures,consequently, and comparison between these two key attention functionsis more direct.

Direct measures of distractor processing: Direct measures of distractorprocessing provide a more accurate assessment of how distractors arebeing processed, than indirect methods such as inferring their level ofprocessing from their impact on target processing. In addition, theimpact on target processing and attention-related processes can also beanalyzed.

Simultaneous: Measuring (the allocation of resources to) both attendingand ignoring in parallel makes it possible to accurately monitor theeffects of fluctuations in arousal and control upon both attending andignoring. It also makes it possible to assess the relationship betweenchanges in attending with respect to ignoring.

Continuous: Not interrupted by probes or other rare events that tend toreset attention, thereby obtaining more natural data on the waxing andwaning of sustained attention. Additional assessment tools may addprobes or different types of continuous tasks as well.

In some embodiments, SSVEPs serve as indices of target and distractorprocessing. These measures are employed to reflect processing ofrelevant (target) and irrelevant (distractor) information.

This protocol leverages an EEG sensing method (SSVEPs) to provide twoimportant key advantages for functional measures of attention: (1)provides continuous electrophysiological tracking of sustained attentionwith high temporal resolution; and (2) provides continuous tracking ofthe levels of BOTH attention to targets and suppression of distractorssimultaneously, as well as performance on a CPT task.

Steady State Visual Evoked Potentials (SSVEPs) are EEG measures of thesignals from cortical brain regions that respond in synchrony with aflickering visual stimulus, the signals represent brain responses thathave reached a steady-state relationship with visual stimulus. FrequencyTagging uses more than one stimulus, each stimulus flickering at adifferent frequency, so that a particular frequency is an index of thatstimulus. Similarly, the SSVEPs at each frequency are an index of thebrain response to the stimulus flickering at that frequency. This allowsus to “Tag” a brain response as being an index of the brain processingof a specific stimulus in the visual scene. For example, one visualstimulus can flicker at 15 Hz and serve as the stimulus to be attendedin our task, and the other, distractor stimulus (to be ignored) canflicker at 20 Hz. By recording the SSVEPs at these two frequencies (15Hz and 20 Hz) we have brain electrophysiological indices of the amountof brain processing of the attended target stimulus (15 Hz SSVEP) andthe ignored distractor stimulus (20 Hz SSVEP).

Using SSVEP to compute attention can be implemented by presenting faintmarker stimuli that flicker on the screen and to superimpose upon themarker stimulus other stimuli that serve as the content for the task.For example, on a light grey background dark grey circular patches canbe presented on the left and right of fixation, flickering at 15 and 20Hz, respectively. Superimposed upon these two patches can be red letters(or other characters) at a rate that is typical in an attention task,e.g. one per second, and the subject is asked to attend to the lettersin the left circular patch and ignore the letters in the right circularpatch. Note that the signals of interest are the two SSVEPs coming fromthe two patches, not the small transient responses to the red letters.Additional assessment tools may use single trial analyses of transientresponses to targets and distractors and their changes over time aswell.

Attention causes the SSVEP to be much larger when the flicker patchlocation is attended than when it is ignored. This exemplary method ismore effective than transient (brief) attention modes. That is, shorttime epochs (typically about 1 second) are extracted from the attentiontask and then signal averaged to obtain the average signal magnitude forthe stimulus when it is attended and for that same stimulus when it isignored. That is, the continuous data are broken into short epochs thatare then signal averaged. This provides an improved signal to noiseratio, but eliminates all the information about any differences in theSSVEP at different times during the task, i.e. the slow fluctuations inattending and ignoring. Also, using many short intervals of taskperformance (e.g. 5-30 seconds at a time) are typically usedspecifically to avoid fluctuations in ability to pay attention thatarise when one has to sustain attention for more than 30 seconds.Consequently, short time epochs explicitly do not measure thedifferences in attention level (or distractor processing level) that arethought to occur when one pays attention and ignores distractors forextended periods of time, i.e. they do not measure the properties ofsustained attention.

In this exemplary protocol, sensors SSVEPs employs circular patches ofstimuli at an attended and ignored location, and records these signalscontinuously during extended 4 minute runs of sustained attention.Tracking the magnitude of the signals for both the attended stimulus(attending/target magnitude) and the ignored stimulus(ignoring/distractor magnitude) continuously over the 4 minute runs isaccomplished by taking the filtered 15 Hz and 20 Hz SSVEP signals andobtaining the Hilbert transform of the signals over the 4 minute run.The results have shown two novel findings that fit with models ofattention. First, the attended signal and the ignored signal bothfluctuate dramatically (e.g. on the order of 100% amplitudefluctuations) over time periods in the range of 10-30 seconds consistentwith the waxing and waning of sustained attention, and demonstrates thatthere are robust data to work with. Second, the fluctuations of the twosignals are not necessarily in synchrony—this demonstrates thatattending and ignoring are separable processes. The latter point meansthat these measures can be used in principle to track peoples' abilityto sustain attention and to sustain ignoring distractionssimultaneously. This is the basis for the described diagnosticcategories, and styles of attending/ignoring in non-patients, and forsubsequent development of new therapeutics and enhancement methods totarget the new categories of attention disorders and attention styles.

The use of SSVEPs to measure slow fluctuations enables the devices forthe method to be produced inexpensively and used by anyone (i.e., notrequiring knowledge of EEG recordings) so that individual consumers canreadily purchase and use them. This broadens the use of the methodbeyond research, educational and clinical facilities to individualconsumers. This has great impact on assessment of attention control andthe consequent creation of new categories of patients and clinicaldisorders. Nearly all other types of clinical assessments are performedin the clinic greatly limiting the view of the patient'scondition/disorder. Performing assessments in real life conditionsimproves the characterization of the patient's condition and is expectedto lead to much more personalized assessments and to creation of newcategories of clinical diagnosis. Accessibility to individual consumersalso makes it possible to use the method for monitoring treatmenteffects in everyday life contexts, greatly improving accuracy oftailoring treatment to the individual patient. It also makes it possiblefor patients and non-patients to use the method to improve theirattentional awareness and attentional control by training any time andanywhere rather than being limited to a facility for training (e.g.,clinic, school, health spa).

In some embodiments, the target/distractor stimulus parameters and taskhave been developed through pilot tests to create sufficientlydistracting distractors, i.e. they create qualitative experientiallysalient interference to participants. The goal is to have stimulusparameters that create enough difficulty and distractor interferencethat a slight increase in distractor salience (brightness or duration)produces a decrease in accuracy. This ensures that there is a benefit tosuppressing distractors—if the target discrimination is too easy, and/orthe distractors are not sufficiently disruptive, then there is littleneed to suppress distractors. 2) We prefer difficulty level to besubstantially at 100% accuracy, such that any waning of attention ordecrease in distractor suppression will result in a loss in accuracy.This protocol adjusts target and distractor brightness and duration todetermine the stimulus parameters that produce the desired cognitiveeffects. Note the stimulus parameters (other than position) are equalfor target and distractor so that the stimuli do not produce unequalbrain responses.

Why not just use EEG alpha-band measures or fMRI? The same type ofmeasurements could be performed with fMRI approaches in principle,however, it is not known if the signal magnitudes would be large enoughfor evaluation of individual patients and the cost would be prohibitive(on the order of $1,000 per person) and the assessments would be limitedin number (due to expense) and not be available in real worldconditions. These methods are an advance or improvement over usingalpha-band recordings for which it is difficult to identify which signalcorresponds to the attended vs. ignored stimulus, and the magnitude ofthe alpha signal may not be large enough for real-time monitoring. Withalpha it is difficult to use anything other than two widely separatedstimuli (so only spatial location can be used as an index; and can bedifficult to differentiate the responses to task stimuli from otheralpha sources). This method may be extended to examine both the stimulusdriven system of attending/ignoring and other systems related to waxingand waning of arousal etc. that would be reflected by naturallyoccurring alpha simultaneously. It may also be possible to develop otherconfigurations of stimuli, including foreground vs. background;superimposed stimuli; auditory stimuli; effects of contextualinformation, etc. none of which can be used effectively with alphameasures.

In one exemplary embodiment, as illustrated by FIG. 1A, an attentionevaluator and/or trainer 100 includes a computerized processor 150, anoutput device 152 (e.g., video display with speakers), an input device154 (e.g., keyboard, mouse, touchpad, and/or joystick) and a neuralscanner 156 (e.g., headgear with EEG sensors) operatively coupled to thehead 188 of a user 180. FIG. 1B is a top view of head 188 showing aplurality of exemplary locations for scanning SSVEP (Steady State VisualEvoked Potentials) and/or SSAEP (Steady State Auditory EvokedPotentials).

Referring initially to the screenshots 3A and 3B, FIG. 2 is a flowchart200 illustrating an exemplary attention assessment protocol, using anattention evaluator and/or trainer 100, useful for accessing attentioncapability or deficits thereof such as ADHD.

In step 210, output device 152 presents and instructs user 180 to attendto a first visual and/or audial (also referred to as “auditory”)stimulus, such as a visual circle (also referred to as “circular patch”)alternating between lighter circle 320 and darker circle 325, andflickering at a first frequency, generally approximately between 3 Hertzand 40 Hertz, and preferably substantially between 15 Hertz and 18Hertz.

Referring also to the screenshots of FIGS. 4A and 4B, output device 152also presents and instructs user 180 to ignore a second visual and/oraudial stimulus via output device 154, such as another flickering visualcircle alternating between lighter circle 430 and darker circle 435, andflickering at a second frequency, generally approximately between 3Hertz and 40 Hertz, and preferably substantially between 15 Hertz and 18Hertz (see step 220).

In step 230, user 150 may also be provided with an optional suitablefocal cue, such as to focus user's eyes on fixation point 340. In thisexample, the first flickering frequency can be 12 Hertz and the secondflickering frequency can be 16 Hertz, and the fixation point 340 can belocated approximately midway between the attended circle 320 and theignored circle 330.

In some embodiments as illustrated by the respective screenshot 300C andscreenshot 400C, a randomized plurality of targets and/or distractors,e.g. target 352 and/or distractor 452, can be presented to user 180either in attended circle 328 and/or ignored circle 438 (step 240).Presentation frequency of targets and/or optional distractors can beapproximately between one and five seconds, and can be randomized withrespect to presentation rate, location and/or duration. Although squaresare used for targets/distractors in this embodiment, other shapes arealso possible, e.g., circles, ovals, rectangles, polygons, triangles orany other regular or irregular shapes.

The user is instructed to respond to target(s) and to ignore anydistractor(s). Processor 150 optionally computes fluctuation of user'sreaction time to the targets, e.g., target 352 (step 250). Reactiontimes can be measured using input device 154.

Neural scanner 156 measures the user's SSVEP and/or SSAEP (step 260).Neural scanner 156 can be an EEG headset such as the EPOC™ availablefrom Emotiv of San Francisco, Calif. and EEG headset available from Imecof Lueven, Belgium.

In step 270, processor 150 computes the user's attention capabilityusing the fluctuation and/or SSVEP/SSAEP using the above describedprotocol. The computed capability can be provided to the user and/or ahuman therapist for evaluation purposed, and hence can be used fordevelopment of a personalized treatment plan.

This can be computed by frequency tagging, e.g., using a moving windowfast Fourier (FFT) of the EEG to extract the magnitude (e.g., amplitude)of the SSVEP signal over time, thereby yielding a waveform that includesthe infra-slow fluctuations of the SSVEP magnitude over a sustainedperiod of time (e.g., from about five seconds to about two minutes,preferably approximately between 10 seconds and 100 seconds). Note thatthe “raw” SSVEP signal includes measurable representations of the abovedescribed flickering frequencies.

The FFT of the waveform can be used to compute the magnitude of the ISFin an exemplary frequency band (such as 0.01-0.2 Hz). The infra-slowfluctuations of the extracted SSVEP can be used to compose an attentionscore which is useful for example diagnosing ADHD.

This technique results in an attention score that aids clinicians intheir assessment of an individual's capacity to attend and ignoreinputs, in simple form, for example:

A(sub ignore)=Power(infraslow band over time)

A(sub attend)=Power (infraslow band over time)

A(sub performance)=Power (infraslow band over time)

Wherein A is the attention score for each.

These techniques can be summarized by the exemplary equations:

A _(I) =P _(I)(t)_(ISF)   EQUATION A

A _(A) =P _(A)(t)_(ISF)   EQUATION B

A _(P) =P _(P)(t)_(ISF)   EQUATION C

Wherein:

-   -   A=attention score (indicate sub-I=Ignore; sub-A=Attend;        sub-P=Performance)    -   ISF=InfraSlow Fluctuations−very low frequencies, such as from        0.01-0.2 Hz.    -   P(t)=Power over time for the infraslow frequencies

NOTE: The magnitude of the power can be found using a FFT, wavelet orother type of transform.

Other modifications and additions are also possible. For example, themagnitude of the waxing and waning of attention reflected in the ISFmagnitude can also vary over tens of minutes and hours of the day, oracross days or longer periods which can be measured with the ISFmagnitude at different periods.

Alternatively or in addition, a new measure that combines the ISF withother EEG measures can be created by relating the ISF to other EEGmeasures extracted at the same time. For example frontal activity couldbe found that co-varies with the ISF.

Many other modifications and additions are also possible. For example,it may be possible to present targets substantially outside of theattended area, and identify the targets using a color, a shape or analphanumeric character (or any suitable symbol such as an Arabiccharacter or Chinese calligraphic symbol).

There are also alternate methods for explicitly and/or implicitlyincorporating a target with the attended area, such as superimposing a“target” onto the attended area, by, for example, substantiallylengthening/narrowing the duration of the flickering pulse and/orvarying the color, shape and/or size of the attended area.

Referring now to the flowchart of FIG. 5 and the screenshots of FIGS.3A-3C & 4A-4C, attention evaluator and/or trainer 100 can be adapted toprovide both diagnosis and treatment protocols.

In some protocols, as illustrated by step 510, output device 152presents and instructs user 180 to attend to a first visual and/oraudial stimulus, such as a visual circle alternating between lightercircle 320 and darker circle 325, and flickering at a first frequency,generally approximately between 3 Hertz and 40 Hertz, and preferablysubstantially between 15 Hertz and 18 Hertz.

Output device 152 also presents and instructs user 180 to ignore asecond visual and/or audial stimulus via output device 152, such asanother flickering visual circle alternating between lighter circle 430and darker circle 435, and flickering at a second frequency, generallyapproximately between 3 Hertz and 40 Hertz, and preferably substantiallybetween 15 Hertz and 18 Hertz (see step 520).

In some protocols, user 150 may also be provided with a suitable focalcue, such as to focus user's eyes on fixation point 340 locatedapproximately midway between the attended circle 320 and the ignoredcircle 330.

As illustrated by screenshots 300C & 400C, a randomized plurality oftargets and/or distractors, e.g., target 352 and/or distractor 452, canbe presented to user 180 either in attended circle 328 and/or ignoredcircle 438 (step 530). Target(s) and/or optional distractor(s) aregenerally present between approximately one and five seconds, and can bevaried with respect to presentation rate, location and/or duration,depending on the training protocol(s). Although squares are used fortargets/distractors in this embodiment, other shapes are also possible,e.g., circles, ovals, rectangles, polygons, triangles or any otherregular or irregular shapes.

In steps 540 and 550, neural scanner 156 measures the user's SSVEPand/or SSAEP, and the user's reaction time to the distractors may alsobe measured. Processor 150 can compute the user's attention capabilityderived from the SSVEP and/or SSAEP, and/or the fluctuation of userreaction time.

In one exemplary “executive function” training protocol as illustratedby step 560, the presentation of the target(s) and/or optionaldistractor(s) relative to the attended and ignored stimuli are varied toeither draw the user's attention towards and/or away from theattended/ignored stimuli. This can be accomplished by, for example,repeatedly displaying targets(s) and/or optional distractor(s) at one orboth of the attended stimulus and ignore stimulus, while monitoring thereaction time and/or accuracy of the user's response to thedistractor(s).

In a modified exemplary “meta-attention” training protocol asillustrated by step 670 of FIG. 6 , the subject is provided withreal-time feedback about their attending or ignoring level based upontheir SSVEP/SSAEP to the attended or ignored stimulus (respectively),and the subject then learns to be aware of their attending or ignoringlevel, increasing their attentional awareness; the subject then bringstheir attending or ignoring level back to the desired level (step 680),thereby learning how to control their attentional processes. Withrepeated use, the subject learns how to control their level of attendingor ignoring. In other instances, meta-attention training can beaccomplished by feedback provided at the end of a session (historicalfeedback) to teach the subject how to be aware of what their attendingor ignoring was like through retrospective self-reflection. For example,if a subject is presented with a salient distraction during thesustained attention task (e.g., an emotional stimulus), it will capturethe subject's attention and there will be a period of time needed tobring their attention back to the task that will be reflected in theSSVEP/SSAEP level. At the end of a training session on the sustainedattention task, the method (670) will provide feedback by illustratinghow long it took to recover their attention level in the attention taskeach time a salient distractor occurred. By reflecting on those feedbackdata, the subject learns about their attentional control and becomesmore aware of their attention (improved meta-attention) and can thenrepeat the task with heightened awareness to learn better control.Repeated usage (steps 610-680) can be used to increase the subject'sattentional awareness and train them to improve their level ofattentional control over attending and ignoring.

Modifications and additions to the above embodiments are also possible.For example, in some protocols, the flickering pulse width, intensityand/or color of the attended/ignored area(s) can be varied for thepurpose of drawing attention to and away from attended area and/orignored area. Alternatively or in addition, size and/or shape of theattended/ignored areas may be varied for the same purpose.Alternatively, non-spatial differentiation of the attended and ignoredstimulus information can be used, for example natural scenes whereobjects appear without fixed location and one type of object is attendedand another type or class of object is ignored, where the non-spatialproperties of the objects determine their type/class (e.g., color orshape or texture). Another example of non-spatial features that can beused to differentiate attended and ignored stimuli is motion. Forexample one class of moving object (which could include an avatarcontrolled by the subject) is attended, but other moving objects areignored. Sensory modality (e.g., auditory, visual) can be used as anon-spatial feature for differentiation. For example, subjects couldattend to visual objects while ignoring sounds.

Alternatively or in addition, conjunctions of non-spatial and/or spatialproperties can also be used to define attended and ignored stimuli, forexample scenes in which the background is ignored and the foreground isattended; faces that are speaking (visual and auditory) in the leftvisual field (spatial) are attended and faces speaking in the rightvisual field are ignored, or faces that are speaking about one topic areattended and faces speaking about another topic are ignored.Consequently, an enormous range of stereotyped or realistic stimuli canbe used to create desired attentional tasks and cognitive loads, therebyproviding a large range of assessment and training environments that canbe related to everyday life activities. These can include attentiontasks in which the subject builds awareness of control over when andwhat to attend to out of multiple stimulus sources.

Meta-attention or awareness of attention includes the capability tosearch and identify where your mind is (which external input or internalprocess is being attended or ignored). The training teaches how to havebetter awareness of attention (better at searching and identifying)leading to better control of attention. If attention is on the task,then keep it there, if it has been captured by a distraction, then bringit back to the task. Alternatively or in addition, there can be primaryand secondary channels of information and action that need to becoordinated to achieve the overall goals of a task. For example, thiscould require attentional awareness and control in which the subjectattends to a primary stimulus channel, but also a secondary channelwhile ignoring a third class of inputs, i.e. irrelevant distractorstimuli; requiring awareness of the primary stimuli while interleavingattention outside those stimuli to the secondary channel stimuli and notthe distractors. For example, in this scenario there would be threedifferent flicker frequencies, for primary task stimuli, secondary taskstimuli and distractor stimuli. Subjects can learn to take voluntarycontrol over when to switch attention between primary and secondarystimulus channels and to ignore distractors. The SSVEP/SSAEP measuresprovide assessment and feedback on attention levels to both primary andsecondary tasks and ignoring of distractors.

Training meta-attention is greatly benefited when the stimuli and taskscan be readily related to real-life situations so that the improvedattentional awareness and control can be transferred to real worldactivities more readily. The capability to define which EEG signalcorresponds to which stimulus when multiple simultaneous stimuli likethese are presented is not possible with other EEG measures (e.g. eventrelated potentials (ERP) or oscillatory signals such as alpha).

Assessment and training can be performed in many different user-definedcontexts in their real life. User-defined mental state and externalenvironment can be incorporated into the scoring and computations ofattentional control (equations A,B,C and derivatives of these);including comparisons of the magnitudes of attend and ignore ISFs andperformance ISFs measured across different time periods (hours, days,weeks etc.). For example, we have shown in the NIH Award study thatattend and ignore ISFs increase as a person becomes fatigued atperforming a task. Alternatively or in addition, the nature of theexternal environment can create other forms of distraction that the usercan be aware of (quiet office versus noisy bus). Alternatively or inaddition, the impact on attention of social factors can be incorporatedinto assessment and training with this method, including inputs fromsocial media and comparisons with other users or group data.

The within-individual data and across-individual data can be enteredinto large databases and mined for patterns that inform individualassessment and treatment and for clinical characterization ofpopulations and sub-populations, creation of new clinical types andsub-types and possibly even new clinical classifications; as well asdevelopment of new treatments and improvements in personalizedtreatments.

There are also alternate methods for explicitly and/or implicitlyincorporating a target with the attended area, such as superimposing a“target” onto the attended area, by, for example, substantiallylengthening/narrowing the duration of the flickering pulse and/orvarying the color, shape and/or size of the attended area. It may beuseful to also track the error rate by comparing the “correct” responsesto targets versus distractors.

Exemplary platforms suitable for implementing embodiments of attentionevaluators and/or trainers include desktops, towers, laptops, tablets,smart phones, video gaming systems and training systems such as flightsimulators. In addition, suitable visual displays and/or input devicesinclude touchscreens and virtual reality goggles.

For further details of the present invention, please see attachedAppendix A.

While this invention has been described in terms of several embodiments,there are alterations, modifications, permutations, and substituteequivalents, which fall within the scope of this invention. Althoughsub-section titles have been provided to aid in the description of theinvention, these titles are merely illustrative and are not intended tolimit the scope of the present invention.

It should also be noted that there are many alternative ways ofimplementing the methods and apparatuses of the present invention. It istherefore intended that the following appended claims be interpreted asincluding all such alterations, modifications, permutations, andsubstitute equivalents as fall within the true spirit and scope of thepresent invention.

What is claimed is:
 1. In a computerized attention training systemhaving an EEG sensor, a method for measuring and improving attentioncapability comprising: providing a first viewable area to be attended bya user over a sustained time period, the first area flickering at afirst frequency; providing a second viewable area to be ignored by theuser over the sustained time period, the second area flickering at asecond frequency; providing a fixation point to the user, the fixationpoint located substantially between the first viewable area and thesecond viewable area; presenting a plurality of targets inserted intothe first viewable area and the second viewable area; measuring an SSVEP(Steady State Visual Evoked Potentials) of the user substantially duringthe time period; extracting from the SSVEP measurement a first amplitudecorresponding to the attended area, and extracting from the SSVEPmeasurement a second amplitude corresponding to the ignored area; andvarying a presentation rate for the plurality of targets insertedbetween the first viewable area and the second viewable area based on adifference between the first amplitude and the second amplitude.